A Comprehensive Survey and Prospect of Cross-Lingual Summarization Method Research

Cross-lingual summarization technology evolved from pipeline-based methods to today’s end-to-end approaches, although the problem of erroneous propagation is greatly avoided, there are still problems such as unclear nature of cross–lingual summarization, insufficient translation and summarization unification capabilities, scarcity of large-scale high-quality and multi-type datasets, insufficient research and exploration of low-resource cross-lingual summarization, and lack of multi-angle evaluation indicators. Therefore, according to the development context of Cross-lingual summarization, we first briefly introduce the pipeline-based first-translation-to-summarization method and the first-summarization and post-translation method, and then focus on zero-shot learning, multi-task learning, knowledge distillation method, knowledge enhancement method, pre-training framework and cross-lingual summarization method based on compression ratio, and then sort out the research progress of end-to-end Cross-lingual summarization, as well as the research motivation and content of various methods, and conduct in-depth comparative analysis. At the same time, since most of the world’s languages are low-resource, we emphasize and especially sort out the current status of low-resource Cross-lingual summarization research. Finally, we also introduce and analyze the dataset and evaluation indicators of Cross-lingual summarization. At the end we discussed the possible directions of future development and presented our own opinions. Through this comprehensive and in-depth survey, it is hoped that researchers interested in this field, especially in low-resource settings, will be helped to promote the further development of Cross-lingual summarization. © 2024, Taiwan Ubiquitous Information CO LTD. All rights reserved.